This study aimed to investigate the impact of textual enhancement and metalinguistic explanation as focus-on-form tasks tending to encourage the acquisition of nominal clauses (NCs) in English. It explored (a) whether textual enhancement and metalinguistic explanation would promote and enhance the knowledge of NCs, (b) whether these two tasks would differ in terms of enhancing learners' knowled...

Our research explores the possibility of categorizing webpages and webpage genre by structure or layout. Based on our results, we believe that webpage structure could play an important role, along with textual and visual keywords, in webpage categorization and searching.

Object Grammars define mappings between text and object graphs. Parsing recognizes syntactic features and creates the corresponding object structure. In the reverse direction, formatting recognizes object graph features and generates an appropriate textual presentation. The key to Object Grammars is the expressive power of the mapping, which decouples the syntactic structure from the graph stru...

This paper presents the second round of the task on Cross-lingual Textual Entailment for Content Synchronization, organized within SemEval-2013. The task was designed to promote research on semantic inference over texts written in different languages, targeting at the same time a real application scenario. Participants were presented with datasets for different language pairs, where multi-direc...

This paper proposes a methodology for generating specialized Japanese data sets for textual entailment, which consists of pairs decomposed into basic sentence relations. We experimented with our methodology over a number of pairs taken from the RITE-2 data set. We compared our methodology with existing studies in terms of agreement, frequencies and times, and we evaluated its validity by invest...

In this paper, we first compare several strategies to handle the newly proposed three-way Recognizing Textual Entailment (RTE) task. Then we define a new measurement for a pair of texts, called Textual Relatedness, which is a weaker concept than semantic similarity or paraphrase. We show that an alignment model based on the predicate-argument structures using this measurement can help an RTE sy...

In this paper we present a classifier for Recognising Textual Entailment (RTE) and Semantic Equivalence. We evaluate the performance of this classifier using an evaluation framework provided by the PASCAL RTE Challenge Workshop. Sentence–pairs are represented as a set of features, which are used by our decision tree classifier to determine if an entailment relationship exisits between each sent...

We present two regression models for the prediction of pairwise preference judgments among MT hypotheses. Both models are based on feature sets that are motivated by textual entailment and incorporate lexical similarity as well as local syntactic features and specific semantic phenomena. One model predicts absolute scores; the other one direct pairwise judgments. We find that both models are co...